The accurate modeling of the transfer of solar radiation through a cloudy atmosphere is one of the open problems hindering accurate weather prediction and various other technologies. One such technology—the accurate forecast of available solar energy during cloudy days—is a key to viable and economic solar energy production.
The modeling of radiative transfer through a cloud is based on the physical theory of light scattering by micro-particles. Input parameters for light scattering (thus in turn for radiative transfer models) are the size and shape distribution of liquid water droplets (size only) and ice particles (size and shape) in the cloud. However such key parameters are unknown in most cases and have to be empirically “guessed” in even the state-of-the-art radiative transfer models. Unfortunately, given the complexity of cloud physics, there is no reliable model for first principle prediction of cloud particle size/shape distribution. Furthermore while certain experimental methods (such as Ka-band zenith radar operating at around 35 GHz) can measure cloud particle size distribution (but cannot measure shape), they have their limitations and are often too sophisticated and costly to cover continental-wide areas.
The existing technologies for analyzing cloud size/shape distribution are essentially all based on direct measurement. This includes ground or satellite based Radar and Lidar which illuminate the cloud layer with microwave and visible/IR EM waves and detect the waves reflected by the cloud layers. The cloud particle sizes and distributions are then calculated using the reflected signal. Other methods include using aircraft to fly into clouds and collect cloud water or ice particles and then measure the characteristics of the collected particles. Similarly, optical instruments onboard aircraft may be used to directly measure cloud particle size/shape distribution. These technologies are expensive and can only be deployed, infrequently, to limited geographical locations.
Thus, improved techniques for analyzing cloud particle size and shape distribution would be desirable.